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Record W3000112767 · doi:10.1109/tap.2020.2963949

Equivalent Circuit Modeling to Design a Dual-Band Dual Linear-to-Circular Polarizer Surface

2020· article· en· W3000112767 on OpenAlexfundno aff
Parinaz Naseri, Jorge R. Costa, Sérgio A. Matos, Carlos A. Fernandes, Sean V. Hum

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaNatural Sciences and Engineering Research Council of Canada
KeywordsPolarizerEquivalent circuitOpticsCoupling (piping)PhysicsLinear polarizationMulti-band deviceCircular polarizationAxial ratioMaterials scienceComputer scienceTelecommunicationsMicrostripAntenna (radio)Quantum mechanics

Abstract

fetched live from OpenAlex

The working principle of a thin dual-band dual-linear to circular polarizer is presented here. This polarizer not only converts incident linearly polarized (LP) waves to circularly polarized (CP) waves in two frequency bands, but it also reverses the handedness of each signal. The electromagnetic behavior of the cell is carefully analyzed and two equivalent circuit models (ECMs) are presented to model the responses of the cell to linearly polarized waves at normal incidence. The ECMs show how utilizing interlayer coupling can be leveraged to achieve reversed CP senses in two bands using a compact design. Analytical formulas are presented to provide initial values of the ECM components including the mutual coupling inductances. We present measurement results that agree well with the full-wave simulation and the ECM results, thus validating the proposed ECM model.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.251
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2020
Admission routes1
Has abstractyes

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